Foundations of statistical natural language processing
Foundations of statistical natural language processing
Suede: a Wizard of Oz prototyping tool for speech user interfaces
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
SUEDE: iterative, informal prototyping for speech interfaces
CHI '01 Extended Abstracts on Human Factors in Computing Systems
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
Information state and dialogue management in the TRINDI dialogue move engine toolkit
Natural Language Engineering
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
PROFER: predictive, robust finite-state parsing for spoken language
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Optimizing dialogue management with reinforcement learning: experiments with the NJFun system
Journal of Artificial Intelligence Research
Speeding up the design of dialogue applications by using database contents and structure information
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
D3 toolkit: a development toolkit for daydreaming spoken dialog systems
IWSDS'10 Proceedings of the Second international conference on Spoken dialogue systems for ambient environments
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Recently, data-driven speech technologies have been widely used to build speech user interfaces. However, developing and managing data-driven spoken dialog systems are laborious and time consuming tasks. Spoken dialog systems have many components and their development and management involves numerous tasks such as preparing the corpus, training, testing and integrating each component for system development and management. In addition, data annotation for natural language understanding and speech recognition is quite burdensome. This paper describes the development of a tool, DialogStudio, to support the development and management of data-driven spoken dialog systems. Desirable aspects of the data-driven spoken dialog system workbench tool are identified, and architectures and concepts are proposed that make DialogStudio efficient in data annotation and system development in a domain and methodology neutral manner. The usability of DialogStudio was validated by developing dialog systems in three different domains with two different dialog management methods. Objective evaluations of each domain show that DialogStudio is a feasible solution as a workbench for data-driven spoken dialog systems.